Evaluation method

ABSTRACT

The invention is directed to an evaluation method for determining a power reduction due to ageing of at least one photovoltaic module at constant radiation intensity with a measurement of an electric variable that may change after a period of time such as cell current, cell voltage and/or cell power, without additional sensors for measuring the radiation intensity, with the following steps
         fixing at least one class k that can be compared year by year and within which a daily power curve or portions of the daily power curve of the photovoltaic module can be compared to each other due to the radiation intensity and the outside temperature to be expected as well as the radiation time, the class k corresponding to a defined period of a year,   measuring energy output values Ek,n that can be compared year by year from a comparable power curve Pk,n (t) through the variable delivered by the photovoltaic generator so that energy differences are determined on the basis of the classes k, n being the respective year,   indicating a power reduction of the photovoltaic module with respect to one or several previous years from the energy output value E k,n directly delivered by the photovoltaic module by calculating the difference with respect to the energy outputs Ek,i of the years i to be compared,   data of comparable days having a comparable power curve P(t) of the photovoltaic module being observed over several years.

1. FIELD OF THE INVENTION

The invention relates to an evaluation method for determining a powerreduction due to aging of at least one photovoltaic module at constantradiation intensity by measuring an electrical variable that may varyafter a while such as cell current, cell voltage and/or cell powerwithout additional sensors for measuring the radiation intensity.

The power of solar cells or of photovoltaic modules is subject to aging.The loss of efficiency ranges from 10% to 20% over a period of time of20 years.

For mounting, solar cells are combined into modules, so-called solar orphotovoltaic modules or solar panels. After 20 years, a solar moduleonly has 90% to 80% of the power indicated.

2. DESCRIPTION OF THE PRIOR ART

From a study “Pratt R. G. et al: “Power of a 4 kW amorphous-siliconalloy photovoltaic array at Oakland Community College, Auburn Hills,Mich.” XP010750513” it is known to record the efficiency and the energyoutput of the plant over a short period of time. It appears from thestudy that the mere comparison of e.g., the energy output in the samemonth of e.g., two consecutive years does not allow inference on theaging of the PV modules since the values characterizing the energyoutput such as radiation intensity and temperature differ too much.

Methods are known, which are based on artificially accelerated agingtests. These tests are only performed for certain conditions such astemperature and irradiation and are thus usually allocated safetyfactors. Hence, the efficiency a manufacturer guarantees after a certaintime is usually less than the actual efficiency drop. For such tests,additional sensors are moreover utilized for sensing for example thetemperature or radiation intensity.

In practice, the power drop of the solar module is very difficult tofollow over time. It is difficult to locate whether the power drop iswithin the limits indicated by the manufacturer since certain generalconditions are needed for this purpose such as a certain outsidetemperature, precise sensors or calibratable radiation sensors and thelike.

BRIEF SUMMARY OF THE INVENTION

It is the object of the invention to find a method of the type mentionedherein above by means of which a long-term power reduction of solarmodules in an installed solar plant can be readily determined with highaccuracy.

This object is solved by the following method steps:

-   -   fixing at least one class k, which is comparable on a        year-to-year basis, within which a daily power curve or portions        of the daily power curve of the photovoltaic module can be        compared to each other on the basis of the radiation intensity        and the outside temperature to be expected as well as of the        radiation time, said class k corresponding to a defined time        range,    -   measuring energy output values Ek,n that can be compared on a        year-to-year basis from a comparable power curve Pk,n (t) by the        variable delivered by the photovoltaic generator so that energy        differences will be determined on the basis of the classes k, n        being the respective year,    -   indicating a power reduction of the photovoltaic module with        respect to one or more previous years of the energy output value        Ek,n immediately delivered by the photovoltaic module by        calculating the difference from the energy outputs Ek,I of the        comparable years i,    -   data of comparable days having a comparable power curve P(t) of        the photovoltaic module are being observed over several years.

Further advantageous implementations of the invention are characterizedin the dependent claims.

Thanks to the measurement method of the invention, it is possible todetermine very precisely a long-term power reduction without the need ofadditional sensors.

The invention relies on the observation that comparable days in terms ofradiation intensity and temperature of the solar plant can be found overseveral years, these days allowing a reliable statement with regards topower reduction thanks to their comparability. In order to ensurecomparability in terms of solar radiation, it is possible to compareover the years days in which a power curve P(t) is almost identical forexample. Since the radiation intensity and the radiation time fluctuatein the course of a year, the year is divided in several periods, i.e.,in several classes k. k may for example be equal to 52 so that thecomparison may be made weekly. The actual comparison then only occurswithin one class k over the years n.

Accordingly, the invention relies on the idea consisting in observingthe energy output of the solar plant over several years. Actual data arecompared with the values in previous years. This allows locating inwhich way the energy output decreases over the years.

In every year, the days must be found at which the energy output of thesolar plant is comparable with values of previous years in order to becapable of making a reliable statement in terms of power reduction.

Accordingly, for each year n, there may be a maximum of k energy values.These energy values can be compared to the energy values of a previousyear, for example to those of the previous year or of the first year.The difference between the energy values is for example a measure of thepower reduction. This difference can be normalized. The energy amount ofthe previous year may serve as a standard.

Accordingly, the invention allows observing over the years powerreduction within one class. Thanks to this accurate measurement, a solarplant can thus be connected for a longer time to a grid withoutmaintenance works. It is also possible to locate early increased powerreduction so that photovoltaic modules can be exchanged in time.

To measure the energy output, a variable of the generator such as thegenerator current, the generator voltage or the generator power can bemeasured.

In an advantageous embodiment of the measurement method of theinvention, there are provided at least two classes k, which aredistributed over the year and within which the daily power curves or theportion of the daily power curve are comparable on the basis of theradiation intensity and the outside temperature as well as of theradiation time. This allows for taking into consideration the seasonalfluctuations of the radiation intensity and of the outside temperatureas well as of the irradiation time to be expected.

Sensing or filing a daily curve of the power P of the generator as wellas of the energy output E of the photovoltaic generator of the day isparticularly advantageous, a day power curve P(t) being determined, thecourse of which is comparable to at least one day curve Pk,n(t) fromprevious years. Accordingly, a measurement of the day curve of the powerof the solar generator P(t) as well as of the daily energy output Etag,i.e., of the two variables is advantageous. These values can be recordedand filed in a data bank, for example by means of a data logger. Withineach class k, one day power curve Pk,n(t) the course of which iscomparable to the day power curves Pk,i(t) from previous years can bedetermined for each year n. This also means that at most k energy outputvalues Ek,n are determined for each year, said energy output valuesbeing compared to the energy output values Ek,I of the previous years i,for example the first year values Ek, 1 so that at the most k values aredetermined for the energy differences ΔEk,n. At least one of theseenergy differences ΔEk,n related to an energy output value Ek,i of aprevious year, for example of the first year Ek,1 is used to indicatethe power reduction of the solar generator.

Accordingly, within each class, one day or one measurement period isdetermined the power curve P(t) and the energy output E of which iscomparable to measurements performed in earlier days.

It is advantageous that a number ktmax of day classes kj is formed. Theday classes correspond to time periods that are associated with fixedtime intervals and that are distributed over the daily sunshine periodto be expected. This comparison then occurs between measurementintervals comprising both the same k and kj classes. One class may alsobe a class having a same pair of coefficients (k, kj) or a same tuple.In the variant widened to include the day classes, there is a maximum ofk*kj energy values E((k,kj),n), which are compared to the energy valuesof the previous years. Differences and averages can be calculated here.

In an advantageous embodiment of the invention, comparable days aredetermined within one class in two steps at most, namely by calculatingand evaluating the first derivation Pk′(t) of the function Pk(t).

The first derivation Pk′(t) of the data host Pk(t) is hereby calculatedand it is checked whether certain limit values have been respected. Ifthese limit values are exceeded or not reached, it can be assumed thatthis day was cloudless.

Alternatively, the first derivation Pk′(t) is calculated and evaluatedby testing a curve area included therein for fixed limit values. In afirst step, the first derivation Pk′(t) then enters an evaluation methodwhich yields values that are not allowed to exceed or fall short ofimposed limit values.

Using a plausibility criterion, it can be clearly determined in a secondstep whether the day is really cloudless. One plausibility criterion mayfor example be measurement data from the data host Pk(t) lying withintolerance bands such as a tolerance band for a certain region or atolerance band for summer days and one for winter days. This means thatthis plausibility criterion is applied to the data host P(t) forexample.

An alternative plausibility criterion is applied to the energy outputEk,tag. The energy output Ek,tag is not allowed to fall short of animposed limit value either.

As an alternative or in addition thereto zero crossings of the firstderivation Pk′(t) are advantageously evaluated in anotherimplementation. A day is clearly cloudless if there is only one zerocrossing. This evaluation method can be performed in only one step.

It is further sensible to impose limit values in the first year and toverify these limit values in the following years.

In another advantageous developed implementation of the method of theinvention there is provided that at least one average value ΔEmittel iscalculated from the k energy difference values ΔEk,n for the year n as ameasure for power reduction. By calculating the average, it is possibleto make a very precise statement about the aging condition of the solarcells. The advantage of this way of proceeding is that quotients orpercentage values obtained thereby, meaning daily and weekly values, canbe averaged both for the k and for the kj classes. One thus obtains avery wide statistical basis, which ensures good accuracy of the values.

A particular benefit is obtained if a daily power curve is determined,which substantially comprises a daily power maximum. This case occurs ifthe day is cloudless. In this variant of the invention, only energyvalues from measurement periods are compared in which there was noshadow. Shadowing can be recognized with the methods mentioned hereinabove.

In this variant, time periods of shadow are recognized by evaluating thechange in luminosity occasioned by passing clouds. In principle, onelocates the change in luminosity by calculating the derivation of thepower generated by the solar plant with respect to time. High values ofsuch a derivation are evaluated by an evaluation algorithm whichcalculates whether the time range of the measurement was influenced byclouds. An effect of benefit is obtained by implementing an evaluationstandard through fix or adaptive threshold values. An evaluationstandard with amount averages, quadratic averages or other values can beutilized. An advantage is obtained if a time range with shadowing isrecognized by comparing the amount of power or energy generated in thetime range with a comparative value. If there are significant negativedifferences, there were shadows. Such a comparative value can begenerated from a model of radiation on a cloudless day. A comparativevalue can also be calculated from the radiation values of previous days,in particular if these corresponding time intervals were recognized tobe cloudless. An effect of benefit is obtained if a comparative value iscalculated from values of previous years that have been stored.

An exemplary embodiment will be described in closer detail withreference to the drawings, additional developed implementations of theinvention and advantages thereof being described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

In said drawings:

FIG. 1 a shows a matrix for several years 1 through n as well as severalclasses 1 through k showing energy outputs,

FIG. 1 b shows a matrix comparable to that of FIG. 1 a, this matrix nowshowing the energy differences,

FIG. 2 a shows a measured curve of the power P of a photovoltaicgenerator for a cloudless day,

FIG. 2 b shows a schematic course of the curve shown in FIG. 2 a,

FIG. 2 c shows the course of the first derivation for the function shownin FIG. 2 b,

FIG. 3 a shows a measured gradient of the power P of the photovoltaicgenerator for a day with passing clouds, is FIG. 3 b shows a schematiccurve of the power shown in FIG. 3 a for the day with passing clouds,

FIG. 3 c shows the course of the first derivation for the function shownin FIG. 3 b,

FIG. 4 a shows the measured course of the power P of the photovoltaicgenerator for a cloudy day,

FIG. 4 b shows the schematic curve of the power P for this day withovercast sky,

FIG. 4 c shows the curve of the first derivation for the function shownin FIG. 4 b.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 a illustrates a matrix with energy output data for several years1 through n, which are indicated in the matrix lines as well as forseveral classes 1 through k, which are indicated in the columns. Theformulae below the matrix indicate the energy differences for each classk and for the respective year n. For each year n, one then has k energyvalues E_(k,n). These energy values passing clouds can then be comparedto the energy values E_(k,l) of the year before i, of any previous yearor of the first year. The difference ΔE_(k,n)=E_(k,i)−E_(k,n) is takento measure the power reduction. This difference can be normalized. Theenergy output of the year before i can for example serve as a standardso that the power reduction can be expressed byΔE_(k,n)/E_(k,i)=(E_(k,i)−E_(k,n))/E_(k,l) As a result, a powerreduction of the photovoltaic modules can be observed within one classover several years.

Accordingly, in FIG. 1 a, ΔE_(1,n) through ΔE_(k,n) signify energydifferences for each class. ΔE*_(l,n) means normalized energydifferences for each class; this will be explained in closer detaillater.

In accordance with the invention, the method is based on the measurementor on the acquisition of the daily curve of the power of the solargenerator P(t) as well as on a daily energy output Etag. These data canbe stored in a data bank.

Distributed over the year, there are several classes k. Two classes kare required though. This is beneficial in order to take into account aseasonal radiation intensity as well as a seasonal dependent outsidetemperature.

Within each class k, a power curve Pk,n(t) is determined for each yearn, said curve having a course that is comparable with the daily powercurves Pk,I of previous years i.

I.e., for each year, a maximum number k of energy output values E_(k,n)are ascertained, which are compared to the energy output values E_(k,I)of the previous years, for example with the energy output valuesE_(k,l), so that a maximum number k of values is determined for theenergy differences ΔE_(k,n).

At least one of these energy differences ΔE_(k,n) related to an energyoutput value E_(k,l) of a previous year i, for example of the first yearvalue E_(k,l), is used to indicate the power reduction of thephotovoltaic generator.

Preferably, the energy outputs are related to one day. I.e., within eachclass one ascertains a day the power curve P(t) and the energy output Eof which are comparable with measurements performed in earlier days. Foreach year n, one then has k energy values E_(k,n), which relate to oneday. These daily energy values E_(k,n) can then be compared with thedaily energy values E_(k,n−1) of the year before or with the energyvalues E_(k,l) of the first year or of any year.

In FIG. 1 b there is shown another matrix which includes the energydifferences for several years 1 through n as well as for all classes 1through k. Below the matrix, there is shown a measurement graph showingthe energy differences ΔE related to the years 1 through n.

From these variables, mean values from all the k energy differencesΔ(E_(k,n)) can be acquired for one year n, namely with the formula:

${\Delta \; E_{{mittel},n}} = {\frac{1}{k} \cdot {\sum\limits_{m = 1}^{k}{\Delta \; E_{m,n}}}}$

For normalized energy differences, the above mentioned formula takes thefollowing form:

${\Delta \; E_{{mittel},n}^{*}} = {\frac{1}{k} \cdot {\sum\limits_{m = 1}^{k}{\Delta \; E_{m,n}^{*}}}}$

Then, the values ΔE_(mittel,n) or ΔE*_(mittel,n) indicate a yearlyaverage value for power reduction of the photovoltaic generator in therespective year n.

It is also possible to consider quadratic averages or an average to thepower of p, i.e., Δ(E_(k,n))^(p) or Δ(E_((k,kj),n))^(p). As a result, asignificant change in the values is possible through which the ageingprocess of the cells can be normalized. An effect of benefit is obtainedif p is a constant comprised between 2 and 6. Herein after, location isdescribed for comparable days.

The FIGS. 2 a, 3 a and 4 a show different daily power curves P(t) fordifferent weather conditions. In FIG. 2 a, the measured power curve isbased on a cloudless day. In FIG. 3 a, a measured curve of the power Pof the solar generator is shown as a function of the time for a day withpassing clouds, the sun irradiating periodically the photovoltaicgenerator through holes in said clouds. In FIG. 4 a, the measured curveof the power P of the solar generator relates to a very cloudy day or toa day with constant weak solar radiation.

As shown in FIG. 2 a, the radiation power of the sun increases atsunrise. About noon, it reaches its maximum peak. Toward sunset, theradiation falls toward zero again. FIG. 2 a accordingly illustrates themeasured curve of the power P of a photovoltaic generator or of one ormore photovoltaic modules as a function of time t for a cloudless day.As can be seen from the curve, there is only one daily maximum withrespect to power P. There is no power break due to passing clouds.

In FIG. 3 a it can be seen that there are strong power fluctuations. Theintensity of the radiation of the photovoltaic modules, which haschanged because of the passing clouds, can be seen clearly.

If a day generates a curve as shown in FIG. 4 a, the day is for examplecloudy or rainy and the solar radiation quite low. Typically, this maybe a winter day.

Accordingly, the FIGS. 2 a, 3 a and 4 a show typical measured powercurves

P(t) for days with different weather conditions, these being in discreteform, i.e., they constitute effective measured variables. Forsimplicity's sake, these functions are shown schematically or ascontinuous functions in the FIGS. 2 b, 3 b and 4 b. The discretemeasurement data can also be transformed into continuous functionsthrough appropriate interpolation methods.

Preferably, in a first step, the first derivation P′(t) of the powercurve P(t) is formed and evaluated for each day, as shown in the FIGS. 2c, 3 c and 4 c.

FIG. 2 b shows the cloudless, sunny day. A plurality of measurementresults are filed in a data bank over the day.

These results are shown in the curve through measurement points on thecurve. The curve has a day maximum peak, which is typically about noon.The area below the curves corresponds to the curve integral or to theenergy.

FIG. 3 b schematically shows the power curve for passing clouds. A kindof harmonics, which are generated by the periodical shadowing throughthe clouds, are superimposed on a basic curve, which corresponds to thecurve in FIG. 2 b.

In order to be capable of determining a power reduction of the solarmodule with very high accuracy, data having a comparable power curveP(t) of the photovoltaic module or of the solar plant are preferablyobserved over several years. As they are comparable, it is possible tomake a reliable statement with respect to power reduction of thephotovoltaic module. In principle, completely cloudy days as illustratedin FIG. 4 a or 4 b or days with passing clouds as shown in the FIG. 3 aor 3 b are in principle suited for comparison. A comparison withcloudless days is however preferred, i.e., a curve as shown in FIG. 2 aor 2 b is compared year by year.

The measurement method preferably uses the power curve P(t) as well asthe energy output E that corresponds to the area enclosed by the curve.This area is hatched in the FIGS. 2 b, 3 b and 4 b. Both are evaluated.Through this measurement method, additional information such as outsidetemperature or radiation data is not needed. Sensors are not neededeither since the power data are measured from the variable of thephotovoltaic module that has been delivered. A voltage, a current orboth can be measured. It is also possible to directly measure the power.

The FIGS. 2 c through 4 c show the first derivation P′(t) of thefunctions shown in the FIGS. 2 b through 4 b.

FIG. 4 b shows an example for the curve of the power of the photovoltaicgenerator as a function of time (t) for a day with overcast sky. In FIG.4 c, there is for example shown the associated first derivation withrespect to time. As opposed to a cloudless day, the maximum power Pmaxcan however be significantly less.

In a first step, the function P′(t) is formed.

The first derivation P′(t) can be evaluated in different ways. Theevaluation clearly indicates whether the day is cloudless or not, asshown in FIG. 3 c.

In a second step, one then analyzes and makes certain whether acloudless day has indeed been found. For this purpose, the power curveP(t) or its first derivation P′(t) is evaluated. Preferably, twoevaluation steps are utilized in order to reliably acquire a comparablecloudless day.

In one of the steps, the first derivation P′(t) is evaluated. For thispurpose, there are two possibilities of evaluating the first derivationP′(t). A first possibility is based on the fact that the evaluationmethod is based on analyzing a maximum for P′(t). If, as shown in FIG. 2c, the maximum value P′max is for example below an imposed limit (upperdashed line) or if the minimum value P′min is above an imposed limitP′min (lower dashed line), it is supposed that the day is cloudless.

As shown in FIG. 3 c, the first derivation of the power curve for a daywith passing clouds has a much higher maximum value P′max but also amuch lower minimum value P′min than the first derivation of the powercurve for a cloudless day shown in FIG. 2 c. In the FIGS. 2 c, 3 c and 4c, the upper limit P′max and the lower limit P′min are also shown asdashed lines. Such limit values can also be defined for certain regions.This is possible because average radiation values are known in principlefor all the regions in a country. Since radiation values are not onlyknown for regions but also e.g., for certain cities, fine-tuning ispossible. These limit values are advantageously acquired and fixed fore.g., a cloudless day in the first year the plant is in operation. Then,verification is performed in the course of the years. Thus, evenlong-term climatic changes in a region due to climate change can betaken into consideration.

As shown in FIG. 4 c, the values of the first derivation of the powercurve for an overcast day are also below or above the imposed limits.Another criterion can be readily used to undoubtedly and automaticallylocate a cloudless day. This is advantageous because a completely cloudyday yields a daily power curve P(t) that is similar to that of acloudless day.

A second possibility of evaluating the first derivation P′(t) isdescribed herein after. In this variant of the evaluation method, P′(t)is also formed from the power curve P(t) for each day.

For each day, the integral is for example determined

$I = {\frac{1}{Tag}{\int_{Tag}{\left( \frac{{P^{\prime}(t)}}{t} \right)^{2}\ {t}}}}$

If the value I acquired lies below a maximum allowable limit I_max sothat I<I_max, it can be assumed that the day is cloudless and this daycan be included in calculating the power reduction. This limit isobtained from typical radiation values and depends for example on thegeographical situation. The corresponding day is then fixed according tothe same pattern as in the previous example of the evaluation method ofP′(t).

The integral I is a measure for the area included in the firstderivation P′(t). A comparison between the FIGS. 2 c and 4 c clearlyshows that the area enclosed by the curve is significantly smaller on acloudy day. This area is determined by the integral I. This means, ifI<I_max, the day may also be cloudy. Therefore, it is appropriate toperform an additional evaluation step.

In another possibility of evaluating the first derivation P′(t), onlythe zero crossings of the P′(t) are taken into consideration. If the dayis for example cloudless, the number of zero crossings of the curve P(t)is equal to 1. This zero crossing takes place at the time of powermaximum, as shown in FIG. 2 c. If more than one zero crossing islocated, as is illustrated in FIG. 3 c, it can be assumed that the dayis not cloudless.

Herein after, the second step of evaluating the power curve P(t) isdescribed in closer detail.

Since in the first step it is at first only supposed that the day iscloudless or not, this must be confirmed in a second step.

There are different variants to achieve this. The first possibility isto evaluate the daily power curve P(t) in the second step.

The first method for evaluating the daily power curve P(t) consists indetermining the daily energy output Etag and in comparing it with animposed minimum value. If the daily energy output Etag exceeds thisminimum value, it is certain that the day is cloudless.

The second evaluation method in the second step consists in evaluatingthe extreme values of the power curve P(t). For this purpose, anabsolute value of the power Pabs is acquired from the host of data P(t)measured within one day. It may for example be the maximum value Pmax ofthe power P(t) for the day observed or also an average of several powermaxima. If this value Pabs lies within a tolerance band ranging fromPabs_min to Pabs_max, then it may well be a relatively cloudless day.Indirectly one also considers the radiation intensity and the durationwithout the need for an additional sensor.

This method can be even further improved by using the measurement or themeasurement values of the temperature of the modules and/or of theoutside temperature.

1. An evaluation method for determining a power reduction due to ageingof at least one photovoltaic module at constant radiation intensity bymeasuring an electric variable that may change after a period of timesuch as cell current, cell voltage and/or cell power without additionalsensors for measuring the radiation intensity with the following stepsfixing at least one class k that can be compared year by year and withinwhich a daily power curve or portions of the daily power curve of thephotovoltaic module can be compared to each other due to the radiationintensity and the outside temperature to be expected as well as theradiation time, the class k corresponding to a defined period of a year,measuring energy output values Ek,n that can be compared year by yearfrom a comparable power curve Pk,n (t) through the variable delivered bythe photovoltaic generator so that energy differences are determined onthe basis of the classes k, n being the respective year, indicating apower reduction of the photovoltaic module with respect to one orseveral previous years from the energy output value E k,n directlydelivered by the photovoltaic module by calculating the difference withrespect to the energy outputs Ek,i of the years i to be compared, dataof comparable days having a comparable power curve P(t) of thephotovoltaic module being observed over several years.
 2. The evaluationmethod as set forth in claim 1, characterized by acquiring and/or filinga daily curve of the power P(t) of the generator as well as of theenergy output E of the day for the generator, in particular in a databank, determining a daily power curve Pk,n(t) the course of which iscomparable at least with a daily power curve Pk,i(t) from previous yearsi and filing the daily output curve Pk,n(t) found and the energy outputEk,n in a data bank.
 3. The evaluation method as set forth in claim 1,characterized by forming daily classes kj, which are allocated to fixedtime intervals of a day.
 4. The evaluation method as set forth in claim1, characterized by forming and evaluating a first derivation of thefunction P(t).
 5. The evaluation method as set forth in claim 1,characterized in that only energy output values are compared which comefrom measurement periods comprising only one daily power peak.
 6. Theevaluation method as set forth in claim 1, characterized in that datawith comparable power curve P(t) of the photovoltaic module are observedover several years.
 7. The evaluation method as set forth in claim 4,characterized by determining comparable days in one step by determiningand evaluating the number of zero crossings of the first derivationP′(t) is determined and evaluated.
 8. The evaluation method as set forthin claim 4, characterized by determining comparable days in two steps bya. evaluating the first derivation P′(t) of the function P(t) using afirst criterion and b. evaluating the daily power curve P(t) using asecond criterion.
 9. The evaluation method as set forth in claim 8,characterized by the first criterion for evaluating the first derivationP′(t) by the fact that the extreme values of the first derivation P′(t)will not exceed an upper limit value P′max and will not fall below alower limit value P′min or that the area included by the curve of thefirst derivation P′(t) will not exceed a fixed limit value.
 10. Theevaluation method as set forth in claim 8, characterized by the secondcriterion for this evaluation of the daily power curve P(t) by the factthat the daily energy output Etag is formed and that this daily energyoutput lies above a fixed limit value or that the maximum of the dailypower curve P(t) lies within a tolerance band Pabs_min and Pabs max. 11.The evaluation method as set forth in claim 1, characterized byspecifying limit values in the first year of measurement and verifyingthe limit values in the following years.
 12. The evaluation method asset forth in claim 1, characterized by acquiring at least one averagevalue ΔEmittel,n from the k energy output difference values ΔEk,n forthe year n as a measure for power reduction.
 13. A solar plant withmeans for carrying out the measurement method as set forth in claim 1.